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DrySim: simulation-aided deployment-specific tailoring of mote-class WSN software

Authors:
Moritz Strübe
FAU, University Erlangen-Nuremberg, Erlangen, Germany
,
Florian Lukas
FAU, University Erlangen-Nuremberg, Erlangen, Germany
,
Bijun Li
TU Braunschweig, Braunschweig, Germany
,
Rüdiger Kapitza
TU Braunschweig, Braunschweig, Germany
Authors Info & Claims
Published: 21 September 2014 Publication History

Abstract

Despite intensive research in the field of mote-class Wireless Sensor Networks in recent years, real-life deployments are still challenging and systems are prone to failures. This can typically be attributed to fragile hardware or misbehaving software. Issues caused by software, often induced by the inherent constraints of resources, can be countered using simulations. However the simulation results often do not reflect those of the specific deployment. We suggest analyzing the actual environment conditions of a deployed network and map them to a simulator. Then, based on simulations, software and parameters can be tailored to the specific deployment. We developed two tool chains, RealSim and DryRun, and compared results from simulation runs to those acquired from two different testbeds using Tmote Sky nodes. This was done in two campaigns, each altering 2 configuration parameters from the hardware to the application layer. The presented data is based on over 1100 experiments, respectively over 270 h, on real hardware and almost 7000 simulations. The close relation of simulation and real measurements shows that our DrySim approach is feasible.

References

[1]
Modelling the impact of software components on wireless sensor network performance. pages 1 -- 6.
[2]
G. Barrenetxea, F. Ingelrest, G. Schaefer, and M. Vetterli. The Hitchhiker's Guide to Successful Wireless Sensor Network Deployments. In Proc. of the 6th ACM conf. on Embedded network sensor systems (SenSys 2008), pages 43--56, 2008.
[3]
L. Bergamini, C. Crociani, A. Vitaletti, and M. Nati. Validation of WSN simulators through a comparison with a real testbed. In Proc. of the 7th ACM workshop on Performance evaluation of wireless ad hoc, sensor, and ubiquitous networks (PE-WASUN 2010), pages 103--104, 2010.
[4]
J. Beutel, K. Römer, M. Ringwald, and M. Woehrle. Deployment Techniques for Sensor Networks. In Sensor Networks, Signals and Communication Technology, chapter Deployment, pages 219--248. Springer, 2009.
[5]
M. Buettner, G. V. Yee, E. Anderson, and R. Han. X-MAC: a short preamble MAC protocol for duty-cycled wireless sensor networks. In Proc. of the 4th int. conf. on Embedded networked sensor systems (SenSys 2006), page 307, 2006.
[6]
M. Chini, M. Ceriotti, R. Marfievici, A. L. Murphy, and G. P. Picco. Demo: TRIDENT, untethered observation of physical communication made to share. In Proc. of the 9th ACM Conf. on Embedded Networked Sensor Systems (SenSys 2011), SenSys '11, pages 409--410, 2011.
[7]
G. Coulson, B. Porter, I. Chatzigiannakis, C. Koninis, S. Fischer, D. Pfisterer, D. Bimschas, T. Braun, P. Hurni, M. Anwander, G. Wagenknecht, S. P. Fekete, A. Kröller, and T. Baumgartner. Flexible experimentation in wireless sensor networks. Communications of the ACM, (1):82--90, 2012.
[8]
DryRun and RealSim authors. Dryrun and realsim git repositories. https://github.com/cmorty/dryrun|realsim.
[9]
A. Dunkels. The contikimac radio duty cycling protocol. Technical report, Swedish Institute of Computer Science, 2011.
[10]
A. Dunkels, B. Grönvall, and T. Voigt. Contiki - a Lightweight and Flexible Operating System for Tiny Networked Sensors. In Proc. of the 1st IEEE Workshop on Embedded Networked Sensors (Emnets-I 2004), 2004.
[11]
A. Dunkels, F. Osterlind, N. Tsiftes, and Z. He. Software-based on-line energy estimation for sensor nodes. In Proc. of the 4th workshop on Embedded networked sensors (EmNets 2007), pages 28--32, 2007.
[12]
J. Eriksson, A. Dunkels, N. Finne, F. Österlind, and T. Voigt. Poster Abstract: MSPsim -- an Extensible Simulator for MSP430-equipped Sensor Boards. In European Conf. on Wireless Sensor Networks (EWSN 2007), Poster/Demo session), pages 1--2, 2007.
[13]
K. Garg, A. Förster, D. Puccinelli, and S. Giordano. Towards Realistic and Credible Wireless Sensor Network Evaluation. In Proc. of the 3rd Int. ICST Ad Hoc Networks (ADHOCNETS 2011), pages 49--64, 2011.
[14]
C. Guo, M. Jacobsson, and R. V. Prasad. A Case Study of Networked Sensors by Simulations and Experiments. In Proc. of the 11th Int. Conf. on Thermal, Mechanical Multi-Physics Simulation, and Experiments in Microelectronics and Microsystems (EuroSimE 2010), pages 1--5, 2010.
[15]
G. P. Halkes and K. G. Langendoen. Experimental evaluation of simulation abstractions for wireless sensor network MAC protocols. EURASIP Journal on Wireless Communications and Networking, pages 24:1---24:2, 2010.
[16]
D. He, G. Mujica, J. Portilla, and T. Riesgo. Simulation tool and case study for planning wireless sensor network. In Proc. of the 38th Annual Conf. on IEEE Industrial Electronics Society (IECON 2012), pages 6024 --6028, 2012.
[17]
P. Hurni and T. Braun. Calibrating Wireless Sensor Network Simulation Models with Real-World Experiments. In Proc. of the 8th Int. IFIP-TC 6 Networking Conf., LNCS, pages 1--13, 2009.
[18]
A. Kamthe, M. A. Carreira-Perpinán, and A. E. Cerpa. M&M: Multi-level Markov Model for Wireless Link Simulations. In Proc. of the 7th ACM Conf. on Embedded Networked Sensor Systems (SenSys 2009), SenSys '09, pages 57--70, 2009.
[19]
E. Kolega, V. Vescoukis, and D. Voutos. Assessment of network simulators for real world WSNs in forest environments. In Proc. of the 2011 IEEE Int. Conf. on Networking, Sensing and Control (ICNSC 2011), pages 427 --432, 2011.
[20]
P. Levis, S. Madden, J. Polastre, R. Szewczyk, K. Whitehouse, A. Woo, D. Gay, J. Hill, M. Welsh, E. Brewer, and D. Culler. TinyOS: An Operating System for Sensor Networks. In Ambient Intelligence, pages 115--148. Springer, 2005.
[21]
Q. Li, F. Österlind, T. Voigt, S. Fischer, and D. Pfisterer. Making wireless sensor network simulators cooperate. In Proc. of the 7th ACM workshop on Performance evaluation of wireless ad hoc, sensor, and ubiquitous networks (PE-WASUN 2010), pages 95--98, 2010.
[22]
A. Marchiori, L. Guo, J. Thomas, and Q. Han. Realistic performance analysis of WSN protocols through trace based simulation. In Proc. of the 7th ACM workshop on Performance evaluation of wireless ad hoc, sensor, and ubiquitous networks (PE-WASUN 2010), pages 87--94, 2010.
[23]
G. Möstl, R. Hagelauer, G. Müller, and A. Springer. A Network and System Level Approach towards an Accurate Simulation of WSNs. In Computer Aided Systems Theory (EUROCAST 2011), LNCS, pages 17--24. Springer, 2012.
[24]
F. Österlind, A. Dunkels, J. Eriksson, N. Finne, and T. Voigt. Cross-level Simulation in COOJA. In European Conf. on Wireless Sensor Networks (EWSN 2007), Poster/Demo session, 2007.
[25]
H. N. Pham, D. Pediaditakis, and A. Boulis. From Simulation to Real Deployments in WSN and Back. In IEEE Int. Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM 2007), pages 1--6, 2007.
[26]
M. Strübe, S. Böhm, R. Kapitza, and F. Dressler. RealSim: Real-time Mapping of Real World Sensor Deployments into Simulation Scenarios. In Proc. of the 6th ACM int. workshop on Wireless network testbeds, experimental evaluation and characterization (WiNTECH 2011), pages 95--96, 2011.
[27]
M. Strübe, F. Lukas, and R. Kapitza. Demo Abstract: CoojaTrace, Extensive Profiling for WSNs. In Poster and Demo Proc. of the 9th European Conf. on Wireless Sensor Networks (EWSN 2012), pages 64--65, 2012.
[28]
M. Zimmerling, F. Ferrari, L. Mottola, T. Voigt, and L. Thiele. pTunes: runtime parameter adaptation for low-power MAC protocols. In Proc. of the 11th int. conf. on Information Processing in Sensor Networks (IPSN 2012), pages 173--184, 2012.

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  • (2020)Exploiting Link Diversity for Performance-Aware and Repeatable Simulation in Low-Power Wireless NetworksIEEE/ACM Transactions on Networking10.1109/TNET.2020.301605628:6(2545-2558)Online publication date: Dec-2020
  • (2019)Instant: A TSCH Schedule for Data Collection from Mobile NodesProceedings of the 2019 International Conference on Embedded Wireless Systems and Networks10.5555/3324320.3324325(35-46)Online publication date: 25-Feb-2019
  • (2018)Moρϕευς: Simulate Reality for the Orchestration of Deployed Networked Embedded SystemsProceedings of the 2018 International Conference on Embedded Wireless Systems and Networks10.5555/3234847.3234866(145-156)Online publication date: 16-Feb-2018
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  1. DrySim: simulation-aided deployment-specific tailoring of mote-class WSN software

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        cover image ACM Conferences
        MSWiM '14: Proceedings of the 17th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems
        September 2014
        352 pages
        ISBN:9781450330305
        DOI:10.1145/2641798
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        Published: 21 September 2014

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        Author Tags

        1. deployment
        2. simulation
        3. testbed
        4. wireless sensor networks

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        MSWiM '14 Paper Acceptance Rate 32 of 128 submissions, 25%;
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        • (2020)Exploiting Link Diversity for Performance-Aware and Repeatable Simulation in Low-Power Wireless NetworksIEEE/ACM Transactions on Networking10.1109/TNET.2020.301605628:6(2545-2558)Online publication date: Dec-2020
        • (2019)Instant: A TSCH Schedule for Data Collection from Mobile NodesProceedings of the 2019 International Conference on Embedded Wireless Systems and Networks10.5555/3324320.3324325(35-46)Online publication date: 25-Feb-2019
        • (2018)Moρϕευς: Simulate Reality for the Orchestration of Deployed Networked Embedded SystemsProceedings of the 2018 International Conference on Embedded Wireless Systems and Networks10.5555/3234847.3234866(145-156)Online publication date: 16-Feb-2018
        • (2018)SPHERE Deployment Manager: A Tool for Deploying IoT Sensor Networks at Large ScaleAd-hoc, Mobile, and Wireless Networks10.1007/978-3-030-00247-3_27(307-318)Online publication date: 30-Aug-2018
        • (2017)A Model-based Framework for the Situated Design and Deployment of Wireless Embedded SystemsProceedings of the 15th ACM Conference on Embedded Network Sensor Systems10.1145/3131672.3136967(1-2)Online publication date: 6-Nov-2017
        • (2017)Situated Wireless Networks Optimisation Through Model-Based Relocation of Nodes2017 IEEE 14th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)10.1109/MASS.2017.21(389-397)Online publication date: Oct-2017
        • (2016)Source-Node Selection to Increase the Reliability of Sensor Networks for Building AutomationProceedings of the 2016 International Conference on Embedded Wireless Systems and Networks10.5555/2893711.2893729(125-136)Online publication date: 15-Feb-2016
        • (2015)ProFuN TGProceedings of the 2015 IEEE 40th Local Computer Networks Conference Workshops (LCN Workshops)10.1109/LCNW.2015.7365924(751-759)Online publication date: 26-Oct-2015

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        References

        References

        [1]
        Modelling the impact of software components on wireless sensor network performance. pages 1 -- 6.
        [2]
        G. Barrenetxea, F. Ingelrest, G. Schaefer, and M. Vetterli. The Hitchhiker's Guide to Successful Wireless Sensor Network Deployments. In Proc. of the 6th ACM conf. on Embedded network sensor systems (SenSys 2008), pages 43--56, 2008.
        [3]
        L. Bergamini, C. Crociani, A. Vitaletti, and M. Nati. Validation of WSN simulators through a comparison with a real testbed. In Proc. of the 7th ACM workshop on Performance evaluation of wireless ad hoc, sensor, and ubiquitous networks (PE-WASUN 2010), pages 103--104, 2010.
        [4]
        J. Beutel, K. Römer, M. Ringwald, and M. Woehrle. Deployment Techniques for Sensor Networks. In Sensor Networks, Signals and Communication Technology, chapter Deployment, pages 219--248. Springer, 2009.
        [5]
        M. Buettner, G. V. Yee, E. Anderson, and R. Han. X-MAC: a short preamble MAC protocol for duty-cycled wireless sensor networks. In Proc. of the 4th int. conf. on Embedded networked sensor systems (SenSys 2006), page 307, 2006.
        [6]
        M. Chini, M. Ceriotti, R. Marfievici, A. L. Murphy, and G. P. Picco. Demo: TRIDENT, untethered observation of physical communication made to share. In Proc. of the 9th ACM Conf. on Embedded Networked Sensor Systems (SenSys 2011), SenSys '11, pages 409--410, 2011.
        [7]
        G. Coulson, B. Porter, I. Chatzigiannakis, C. Koninis, S. Fischer, D. Pfisterer, D. Bimschas, T. Braun, P. Hurni, M. Anwander, G. Wagenknecht, S. P. Fekete, A. Kröller, and T. Baumgartner. Flexible experimentation in wireless sensor networks. Communications of the ACM, (1):82--90, 2012.
        [8]
        DryRun and RealSim authors. Dryrun and realsim git repositories. https://github.com/cmorty/dryrun|realsim.
        [9]
        A. Dunkels. The contikimac radio duty cycling protocol. Technical report, Swedish Institute of Computer Science, 2011.
        [10]
        A. Dunkels, B. Grönvall, and T. Voigt. Contiki - a Lightweight and Flexible Operating System for Tiny Networked Sensors. In Proc. of the 1st IEEE Workshop on Embedded Networked Sensors (Emnets-I 2004), 2004.
        [11]
        A. Dunkels, F. Osterlind, N. Tsiftes, and Z. He. Software-based on-line energy estimation for sensor nodes. In Proc. of the 4th workshop on Embedded networked sensors (EmNets 2007), pages 28--32, 2007.
        [12]
        J. Eriksson, A. Dunkels, N. Finne, F. Österlind, and T. Voigt. Poster Abstract: MSPsim -- an Extensible Simulator for MSP430-equipped Sensor Boards. In European Conf. on Wireless Sensor Networks (EWSN 2007), Poster/Demo session), pages 1--2, 2007.
        [13]
        K. Garg, A. Förster, D. Puccinelli, and S. Giordano. Towards Realistic and Credible Wireless Sensor Network Evaluation. In Proc. of the 3rd Int. ICST Ad Hoc Networks (ADHOCNETS 2011), pages 49--64, 2011.
        [14]
        C. Guo, M. Jacobsson, and R. V. Prasad. A Case Study of Networked Sensors by Simulations and Experiments. In Proc. of the 11th Int. Conf. on Thermal, Mechanical Multi-Physics Simulation, and Experiments in Microelectronics and Microsystems (EuroSimE 2010), pages 1--5, 2010.
        [15]
        G. P. Halkes and K. G. Langendoen. Experimental evaluation of simulation abstractions for wireless sensor network MAC protocols. EURASIP Journal on Wireless Communications and Networking, pages 24:1---24:2, 2010.
        [16]
        D. He, G. Mujica, J. Portilla, and T. Riesgo. Simulation tool and case study for planning wireless sensor network. In Proc. of the 38th Annual Conf. on IEEE Industrial Electronics Society (IECON 2012), pages 6024 --6028, 2012.
        [17]
        P. Hurni and T. Braun. Calibrating Wireless Sensor Network Simulation Models with Real-World Experiments. In Proc. of the 8th Int. IFIP-TC 6 Networking Conf., LNCS, pages 1--13, 2009.
        [18]
        A. Kamthe, M. A. Carreira-Perpinán, and A. E. Cerpa. M&M: Multi-level Markov Model for Wireless Link Simulations. In Proc. of the 7th ACM Conf. on Embedded Networked Sensor Systems (SenSys 2009), SenSys '09, pages 57--70, 2009.
        [19]
        E. Kolega, V. Vescoukis, and D. Voutos. Assessment of network simulators for real world WSNs in forest environments. In Proc. of the 2011 IEEE Int. Conf. on Networking, Sensing and Control (ICNSC 2011), pages 427 --432, 2011.
        [20]
        P. Levis, S. Madden, J. Polastre, R. Szewczyk, K. Whitehouse, A. Woo, D. Gay, J. Hill, M. Welsh, E. Brewer, and D. Culler. TinyOS: An Operating System for Sensor Networks. In Ambient Intelligence, pages 115--148. Springer, 2005.
        [21]
        Q. Li, F. Österlind, T. Voigt, S. Fischer, and D. Pfisterer. Making wireless sensor network simulators cooperate. In Proc. of the 7th ACM workshop on Performance evaluation of wireless ad hoc, sensor, and ubiquitous networks (PE-WASUN 2010), pages 95--98, 2010.
        [22]
        A. Marchiori, L. Guo, J. Thomas, and Q. Han. Realistic performance analysis of WSN protocols through trace based simulation. In Proc. of the 7th ACM workshop on Performance evaluation of wireless ad hoc, sensor, and ubiquitous networks (PE-WASUN 2010), pages 87--94, 2010.
        [23]
        G. Möstl, R. Hagelauer, G. Müller, and A. Springer. A Network and System Level Approach towards an Accurate Simulation of WSNs. In Computer Aided Systems Theory (EUROCAST 2011), LNCS, pages 17--24. Springer, 2012.
        [24]
        F. Österlind, A. Dunkels, J. Eriksson, N. Finne, and T. Voigt. Cross-level Simulation in COOJA. In European Conf. on Wireless Sensor Networks (EWSN 2007), Poster/Demo session, 2007.
        [25]
        H. N. Pham, D. Pediaditakis, and A. Boulis. From Simulation to Real Deployments in WSN and Back. In IEEE Int. Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM 2007), pages 1--6, 2007.
        [26]
        M. Strübe, S. Böhm, R. Kapitza, and F. Dressler. RealSim: Real-time Mapping of Real World Sensor Deployments into Simulation Scenarios. In Proc. of the 6th ACM int. workshop on Wireless network testbeds, experimental evaluation and characterization (WiNTECH 2011), pages 95--96, 2011.
        [27]
        M. Strübe, F. Lukas, and R. Kapitza. Demo Abstract: CoojaTrace, Extensive Profiling for WSNs. In Poster and Demo Proc. of the 9th European Conf. on Wireless Sensor Networks (EWSN 2012), pages 64--65, 2012.
        [28]
        M. Zimmerling, F. Ferrari, L. Mottola, T. Voigt, and L. Thiele. pTunes: runtime parameter adaptation for low-power MAC protocols. In Proc. of the 11th int. conf. on Information Processing in Sensor Networks (IPSN 2012), pages 173--184, 2012.